Overview
Brought to you by YData
Dataset statistics
| Number of variables | 16 |
|---|---|
| Number of observations | 7770 |
| Missing cells | 0 |
| Missing cells (%) | 0.0% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 971.2 KiB |
| Average record size in memory | 128.0 B |
Variable types
| Text | 8 |
|---|---|
| Categorical | 2 |
| DateTime | 1 |
| Numeric | 4 |
| Unsupported | 1 |
age_on_netflix is highly overall correlated with release_year | High correlation |
release_year is highly overall correlated with age_on_netflix | High correlation |
show_id has unique values | Unique |
title has unique values | Unique |
bigrams is an unsupported type, check if it needs cleaning or further analysis | Unsupported |
age_on_netflix has 2823 (36.3%) zeros | Zeros |
Reproduction
| Analysis started | 2025-09-10 13:41:19.340617 |
|---|---|
| Analysis finished | 2025-09-10 13:41:41.864771 |
| Duration | 22.52 seconds |
| Software version | ydata-profiling vv4.16.1 |
| Download configuration | config.json |
Variables
show_id
Text
Unique
| Distinct | 7770 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Length
| Max length | 5 |
|---|---|
| Median length | 5 |
| Mean length | 4.8580438 |
| Min length | 2 |
Unique
| Unique | 7770 ? |
|---|---|
| Unique (%) | 100.0% |
Sample
| 1st row | s1 |
|---|---|
| 2nd row | s2 |
| 3rd row | s3 |
| 4th row | s4 |
| 5th row | s5 |
| Value | Count | Frequency (%) |
| s11 | 1 | < 0.1% |
| s7787 | 1 | < 0.1% |
| s1 | 1 | < 0.1% |
| s2 | 1 | < 0.1% |
| s3 | 1 | < 0.1% |
| s4 | 1 | < 0.1% |
| s5 | 1 | < 0.1% |
| s6 | 1 | < 0.1% |
| s7 | 1 | < 0.1% |
| s8 | 1 | < 0.1% |
| Other values (7760) | 7760 |
Most occurring characters
| Value | Count | Frequency (%) |
| s | 7770 | |
| 1 | 3357 | |
| 4 | 3354 | |
| 5 | 3352 | |
| 2 | 3351 | |
| 6 | 3350 | |
| 3 | 3344 | |
| 7 | 3129 | |
| 8 | 2252 | 6.0% |
| 0 | 2245 | 5.9% |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 37747 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| s | 7770 | |
| 1 | 3357 | |
| 4 | 3354 | |
| 5 | 3352 | |
| 2 | 3351 | |
| 6 | 3350 | |
| 3 | 3344 | |
| 7 | 3129 | |
| 8 | 2252 | 6.0% |
| 0 | 2245 | 5.9% |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 37747 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| s | 7770 | |
| 1 | 3357 | |
| 4 | 3354 | |
| 5 | 3352 | |
| 2 | 3351 | |
| 6 | 3350 | |
| 3 | 3344 | |
| 7 | 3129 | |
| 8 | 2252 | 6.0% |
| 0 | 2245 | 5.9% |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 37747 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| s | 7770 | |
| 1 | 3357 | |
| 4 | 3354 | |
| 5 | 3352 | |
| 2 | 3351 | |
| 6 | 3350 | |
| 3 | 3344 | |
| 7 | 3129 | |
| 8 | 2252 | 6.0% |
| 0 | 2245 | 5.9% |
Length
| Max length | 7 |
|---|---|
| Median length | 5 |
| Mean length | 5.6172458 |
| Min length | 5 |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | TV Show |
|---|---|
| 2nd row | Movie |
| 3rd row | Movie |
| 4th row | Movie |
| 5th row | Movie |
Common Values
| Value | Count | Frequency (%) |
| Movie | 5372 | |
| TV Show | 2398 |
Length
Histogram of lengths of the category
Common Values (Plot)
| Value | Count | Frequency (%) |
| movie | 5372 | |
| tv | 2398 | |
| show | 2398 |
Most occurring characters
| Value | Count | Frequency (%) |
| o | 7770 | |
| M | 5372 | |
| v | 5372 | |
| i | 5372 | |
| e | 5372 | |
| T | 2398 | 5.5% |
| V | 2398 | 5.5% |
| 2398 | 5.5% | |
| S | 2398 | 5.5% |
| h | 2398 | 5.5% |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 43646 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| o | 7770 | |
| M | 5372 | |
| v | 5372 | |
| i | 5372 | |
| e | 5372 | |
| T | 2398 | 5.5% |
| V | 2398 | 5.5% |
| 2398 | 5.5% | |
| S | 2398 | 5.5% |
| h | 2398 | 5.5% |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 43646 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| o | 7770 | |
| M | 5372 | |
| v | 5372 | |
| i | 5372 | |
| e | 5372 | |
| T | 2398 | 5.5% |
| V | 2398 | 5.5% |
| 2398 | 5.5% | |
| S | 2398 | 5.5% |
| h | 2398 | 5.5% |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 43646 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| o | 7770 | |
| M | 5372 | |
| v | 5372 | |
| i | 5372 | |
| e | 5372 | |
| T | 2398 | 5.5% |
| V | 2398 | 5.5% |
| 2398 | 5.5% | |
| S | 2398 | 5.5% |
| h | 2398 | 5.5% |
title
Text
Unique
| Distinct | 7770 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Length
| Max length | 104 |
|---|---|
| Median length | 71 |
| Mean length | 17.622008 |
| Min length | 1 |
Unique
| Unique | 7770 ? |
|---|---|
| Unique (%) | 100.0% |
Sample
| 1st row | 3% |
|---|---|
| 2nd row | 7:19 |
| 3rd row | 23:59 |
| 4th row | 9 |
| 5th row | 21 |
| Value | Count | Frequency (%) |
| the | 1928 | 8.0% |
| of | 608 | 2.5% |
| a | 306 | 1.3% |
| in | 244 | 1.0% |
| 216 | 0.9% | |
| and | 200 | 0.8% |
| to | 171 | 0.7% |
| love | 151 | 0.6% |
| my | 126 | 0.5% |
| 2 | 113 | 0.5% |
| Other values (8480) | 19906 |
Most occurring characters
| Value | Count | Frequency (%) |
| 16201 | 11.8% | |
| e | 12729 | 9.3% |
| a | 9811 | 7.2% |
| o | 7710 | 5.6% |
| i | 7568 | 5.5% |
| r | 7344 | 5.4% |
| n | 7147 | 5.2% |
| t | 6211 | 4.5% |
| s | 5461 | 4.0% |
| h | 4754 | 3.5% |
| Other values (187) | 51987 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 136923 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 16201 | 11.8% | |
| e | 12729 | 9.3% |
| a | 9811 | 7.2% |
| o | 7710 | 5.6% |
| i | 7568 | 5.5% |
| r | 7344 | 5.4% |
| n | 7147 | 5.2% |
| t | 6211 | 4.5% |
| s | 5461 | 4.0% |
| h | 4754 | 3.5% |
| Other values (187) | 51987 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 136923 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 16201 | 11.8% | |
| e | 12729 | 9.3% |
| a | 9811 | 7.2% |
| o | 7710 | 5.6% |
| i | 7568 | 5.5% |
| r | 7344 | 5.4% |
| n | 7147 | 5.2% |
| t | 6211 | 4.5% |
| s | 5461 | 4.0% |
| h | 4754 | 3.5% |
| Other values (187) | 51987 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 136923 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 16201 | 11.8% | |
| e | 12729 | 9.3% |
| a | 9811 | 7.2% |
| o | 7710 | 5.6% |
| i | 7568 | 5.5% |
| r | 7344 | 5.4% |
| n | 7147 | 5.2% |
| t | 6211 | 4.5% |
| s | 5461 | 4.0% |
| h | 4754 | 3.5% |
| Other values (187) | 51987 |
director
Text
| Distinct | 4048 |
|---|---|
| Distinct (%) | 52.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Length
| Max length | 208 |
|---|---|
| Median length | 179 |
| Mean length | 12.823295 |
| Min length | 2 |
Unique
| Unique | 3311 ? |
|---|---|
| Unique (%) | 42.6% |
Sample
| 1st row | Unknown |
|---|---|
| 2nd row | Jorge Michel Grau |
| 3rd row | Gilbert Chan |
| 4th row | Shane Acker |
| 5th row | Robert Luketic |
| Value | Count | Frequency (%) |
| unknown | 2376 | 15.6% |
| david | 108 | 0.7% |
| michael | 103 | 0.7% |
| john | 82 | 0.5% |
| paul | 64 | 0.4% |
| robert | 48 | 0.3% |
| chris | 46 | 0.3% |
| peter | 44 | 0.3% |
| james | 42 | 0.3% |
| jay | 41 | 0.3% |
| Other values (5898) | 12292 |
Most occurring characters
| Value | Count | Frequency (%) |
| n | 12593 | 12.6% |
| a | 8846 | 8.9% |
| 7476 | 7.5% | |
| o | 6684 | 6.7% |
| e | 6145 | 6.2% |
| i | 5129 | 5.1% |
| r | 4940 | 5.0% |
| k | 3615 | 3.6% |
| l | 3382 | 3.4% |
| h | 2908 | 2.9% |
| Other values (89) | 37919 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 99637 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| n | 12593 | 12.6% |
| a | 8846 | 8.9% |
| 7476 | 7.5% | |
| o | 6684 | 6.7% |
| e | 6145 | 6.2% |
| i | 5129 | 5.1% |
| r | 4940 | 5.0% |
| k | 3615 | 3.6% |
| l | 3382 | 3.4% |
| h | 2908 | 2.9% |
| Other values (89) | 37919 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 99637 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| n | 12593 | 12.6% |
| a | 8846 | 8.9% |
| 7476 | 7.5% | |
| o | 6684 | 6.7% |
| e | 6145 | 6.2% |
| i | 5129 | 5.1% |
| r | 4940 | 5.0% |
| k | 3615 | 3.6% |
| l | 3382 | 3.4% |
| h | 2908 | 2.9% |
| Other values (89) | 37919 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 99637 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| n | 12593 | 12.6% |
| a | 8846 | 8.9% |
| 7476 | 7.5% | |
| o | 6684 | 6.7% |
| e | 6145 | 6.2% |
| i | 5129 | 5.1% |
| r | 4940 | 5.0% |
| k | 3615 | 3.6% |
| l | 3382 | 3.4% |
| h | 2908 | 2.9% |
| Other values (89) | 37919 |
cast
Text
| Distinct | 6818 |
|---|---|
| Distinct (%) | 87.7% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Length
| Max length | 771 |
|---|---|
| Median length | 358 |
| Mean length | 107.66396 |
| Min length | 3 |
Unique
| Unique | 6680 ? |
|---|---|
| Unique (%) | 86.0% |
Sample
| 1st row | João Miguel, Bianca Comparato, Michel Gomes, Rodolfo Valente, Vaneza Oliveira, Rafael Lozano, Viviane Porto, Mel Fronckowiak, Sergio Mamberti, Zezé Motta, Celso Frateschi |
|---|---|
| 2nd row | Demián Bichir, Héctor Bonilla, Oscar Serrano, Azalia Ortiz, Octavio Michel, Carmen Beato |
| 3rd row | Tedd Chan, Stella Chung, Henley Hii, Lawrence Koh, Tommy Kuan, Josh Lai, Mark Lee, Susan Leong, Benjamin Lim |
| 4th row | Elijah Wood, John C. Reilly, Jennifer Connelly, Christopher Plummer, Crispin Glover, Martin Landau, Fred Tatasciore, Alan Oppenheimer, Tom Kane |
| 5th row | Jim Sturgess, Kevin Spacey, Kate Bosworth, Aaron Yoo, Liza Lapira, Jacob Pitts, Laurence Fishburne, Jack McGee, Josh Gad, Sam Golzari, Helen Carey, Jack Gilpin |
| Value | Count | Frequency (%) |
| unknown | 718 | 0.6% |
| michael | 567 | 0.5% |
| john | 500 | 0.4% |
| david | 484 | 0.4% |
| lee | 395 | 0.3% |
| james | 357 | 0.3% |
| paul | 310 | 0.3% |
| kim | 298 | 0.3% |
| khan | 255 | 0.2% |
| de | 253 | 0.2% |
| Other values (30345) | 111562 |
Most occurring characters
| Value | Count | Frequency (%) |
| 107934 | 12.9% | |
| a | 82879 | 9.9% |
| e | 57109 | 6.8% |
| n | 52504 | 6.3% |
| i | 48927 | 5.8% |
| , | 48793 | 5.8% |
| r | 42344 | 5.1% |
| o | 39266 | 4.7% |
| l | 30889 | 3.7% |
| h | 25092 | 3.0% |
| Other values (140) | 300812 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 836549 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 107934 | 12.9% | |
| a | 82879 | 9.9% |
| e | 57109 | 6.8% |
| n | 52504 | 6.3% |
| i | 48927 | 5.8% |
| , | 48793 | 5.8% |
| r | 42344 | 5.1% |
| o | 39266 | 4.7% |
| l | 30889 | 3.7% |
| h | 25092 | 3.0% |
| Other values (140) | 300812 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 836549 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 107934 | 12.9% | |
| a | 82879 | 9.9% |
| e | 57109 | 6.8% |
| n | 52504 | 6.3% |
| i | 48927 | 5.8% |
| , | 48793 | 5.8% |
| r | 42344 | 5.1% |
| o | 39266 | 4.7% |
| l | 30889 | 3.7% |
| h | 25092 | 3.0% |
| Other values (140) | 300812 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 836549 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 107934 | 12.9% | |
| a | 82879 | 9.9% |
| e | 57109 | 6.8% |
| n | 52504 | 6.3% |
| i | 48927 | 5.8% |
| , | 48793 | 5.8% |
| r | 42344 | 5.1% |
| o | 39266 | 4.7% |
| l | 30889 | 3.7% |
| h | 25092 | 3.0% |
| Other values (140) | 300812 |
country
Text
| Distinct | 681 |
|---|---|
| Distinct (%) | 8.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Length
| Max length | 123 |
|---|---|
| Median length | 104 |
| Mean length | 12.444916 |
| Min length | 4 |
Unique
| Unique | 517 ? |
|---|---|
| Unique (%) | 6.7% |
Sample
| 1st row | Brazil |
|---|---|
| 2nd row | Mexico |
| 3rd row | Singapore |
| 4th row | United States |
| 5th row | United States |
| Value | Count | Frequency (%) |
| united | 4549 | |
| states | 3793 | |
| india | 990 | 6.8% |
| kingdom | 722 | 5.0% |
| canada | 412 | 2.8% |
| france | 349 | 2.4% |
| japan | 285 | 2.0% |
| south | 266 | 1.8% |
| spain | 215 | 1.5% |
| korea | 212 | 1.5% |
| Other values (119) | 2784 |
Most occurring characters
| Value | Count | Frequency (%) |
| t | 13008 | |
| e | 10418 | |
| a | 9707 | |
| n | 9118 | |
| i | 8241 | |
| d | 7075 | 7.3% |
| 6807 | 7.0% | |
| U | 4570 | 4.7% |
| S | 4401 | 4.6% |
| s | 4334 | 4.5% |
| Other values (41) | 19018 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 96697 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| t | 13008 | |
| e | 10418 | |
| a | 9707 | |
| n | 9118 | |
| i | 8241 | |
| d | 7075 | 7.3% |
| 6807 | 7.0% | |
| U | 4570 | 4.7% |
| S | 4401 | 4.6% |
| s | 4334 | 4.5% |
| Other values (41) | 19018 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 96697 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| t | 13008 | |
| e | 10418 | |
| a | 9707 | |
| n | 9118 | |
| i | 8241 | |
| d | 7075 | 7.3% |
| 6807 | 7.0% | |
| U | 4570 | 4.7% |
| S | 4401 | 4.6% |
| s | 4334 | 4.5% |
| Other values (41) | 19018 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 96697 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| t | 13008 | |
| e | 10418 | |
| a | 9707 | |
| n | 9118 | |
| i | 8241 | |
| d | 7075 | 7.3% |
| 6807 | 7.0% | |
| U | 4570 | 4.7% |
| S | 4401 | 4.6% |
| s | 4334 | 4.5% |
| Other values (41) | 19018 |
date_added
Date
| Distinct | 1511 |
|---|---|
| Distinct (%) | 19.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
| Minimum | 2008-01-01 00:00:00 |
|---|---|
| Maximum | 2021-01-16 00:00:00 |
| Invalid dates | 0 |
| Invalid dates (%) | 0.0% |
Histogram with fixed size bins (bins=50)
release_year
Real number (ℝ)
High correlation
| Distinct | 73 |
|---|---|
| Distinct (%) | 0.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2013.9354 |
| Minimum | 1925 |
|---|---|
| Maximum | 2021 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 121.4 KiB |
Quantile statistics
| Minimum | 1925 |
|---|---|
| 5-th percentile | 1998 |
| Q1 | 2013 |
| median | 2017 |
| Q3 | 2018 |
| 95-th percentile | 2020 |
| Maximum | 2021 |
| Range | 96 |
| Interquartile range (IQR) | 5 |
Descriptive statistics
| Standard deviation | 8.7643567 |
|---|---|
| Coefficient of variation (CV) | 0.0043518559 |
| Kurtosis | 17.54936 |
| Mean | 2013.9354 |
| Median Absolute Deviation (MAD) | 2 |
| Skewness | -3.6188757 |
| Sum | 15648278 |
| Variance | 76.813949 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 2018 | 1120 | |
| 2017 | 1010 | |
| 2019 | 996 | |
| 2016 | 881 | |
| 2020 | 868 | |
| 2015 | 536 | 6.9% |
| 2014 | 334 | 4.3% |
| 2013 | 265 | 3.4% |
| 2012 | 218 | 2.8% |
| 2010 | 171 | 2.2% |
| Other values (63) | 1371 |
| Value | Count | Frequency (%) |
| 1925 | 1 | < 0.1% |
| 1942 | 2 | |
| 1943 | 3 | |
| 1944 | 3 | |
| 1945 | 3 | |
| 1946 | 2 | |
| 1947 | 1 | < 0.1% |
| 1954 | 2 | |
| 1955 | 3 | |
| 1956 | 2 |
| Value | Count | Frequency (%) |
| 2021 | 31 | 0.4% |
| 2020 | 868 | |
| 2019 | 996 | |
| 2018 | 1120 | |
| 2017 | 1010 | |
| 2016 | 881 | |
| 2015 | 536 | |
| 2014 | 334 | 4.3% |
| 2013 | 265 | 3.4% |
| 2012 | 218 | 2.8% |
rating
Categorical
| Distinct | 14 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
| TV-MA | |
|---|---|
| TV-14 | |
| TV-PG | |
| R | |
| PG-13 | |
| Other values (9) |
Length
| Max length | 8 |
|---|---|
| Median length | 5 |
| Mean length | 4.4496782 |
| Min length | 1 |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | TV-MA |
|---|---|
| 2nd row | TV-MA |
| 3rd row | R |
| 4th row | PG-13 |
| 5th row | PG-13 |
Common Values
| Value | Count | Frequency (%) |
| TV-MA | 2861 | |
| TV-14 | 1928 | |
| TV-PG | 804 | 10.3% |
| R | 665 | 8.6% |
| PG-13 | 386 | 5.0% |
| TV-Y | 279 | 3.6% |
| TV-Y7 | 270 | 3.5% |
| PG | 247 | 3.2% |
| TV-G | 194 | 2.5% |
| NR | 83 | 1.1% |
| Other values (4) | 53 | 0.7% |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| tv-ma | 2861 | |
| tv-14 | 1928 | |
| tv-pg | 804 | 10.3% |
| r | 665 | 8.6% |
| pg-13 | 386 | 5.0% |
| tv-y | 279 | 3.6% |
| tv-y7 | 270 | 3.5% |
| pg | 247 | 3.2% |
| tv-g | 194 | 2.5% |
| nr | 83 | 1.1% |
| Other values (4) | 53 | 0.7% |
Most occurring characters
| Value | Count | Frequency (%) |
| - | 6737 | |
| V | 6348 | |
| T | 6342 | |
| M | 2861 | |
| A | 2861 | |
| 1 | 2317 | 6.7% |
| 4 | 1928 | 5.6% |
| G | 1670 | 4.8% |
| P | 1437 | 4.2% |
| R | 753 | 2.2% |
| Other values (7) | 1320 | 3.8% |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 34574 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| - | 6737 | |
| V | 6348 | |
| T | 6342 | |
| M | 2861 | |
| A | 2861 | |
| 1 | 2317 | 6.7% |
| 4 | 1928 | 5.6% |
| G | 1670 | 4.8% |
| P | 1437 | 4.2% |
| R | 753 | 2.2% |
| Other values (7) | 1320 | 3.8% |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 34574 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| - | 6737 | |
| V | 6348 | |
| T | 6342 | |
| M | 2861 | |
| A | 2861 | |
| 1 | 2317 | 6.7% |
| 4 | 1928 | 5.6% |
| G | 1670 | 4.8% |
| P | 1437 | 4.2% |
| R | 753 | 2.2% |
| Other values (7) | 1320 | 3.8% |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 34574 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| - | 6737 | |
| V | 6348 | |
| T | 6342 | |
| M | 2861 | |
| A | 2861 | |
| 1 | 2317 | 6.7% |
| 4 | 1928 | 5.6% |
| G | 1670 | 4.8% |
| P | 1437 | 4.2% |
| R | 753 | 2.2% |
| Other values (7) | 1320 | 3.8% |
duration
Text
| Distinct | 216 |
|---|---|
| Distinct (%) | 2.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Length
| Max length | 10 |
|---|---|
| Median length | 9 |
| Mean length | 7.0459459 |
| Min length | 5 |
Unique
| Unique | 36 ? |
|---|---|
| Unique (%) | 0.5% |
Sample
| 1st row | 4 Seasons |
|---|---|
| 2nd row | 93 min |
| 3rd row | 78 min |
| 4th row | 80 min |
| 5th row | 123 min |
| Value | Count | Frequency (%) |
| min | 5372 | |
| 1 | 1606 | 10.3% |
| season | 1606 | 10.3% |
| seasons | 792 | 5.1% |
| 2 | 378 | 2.4% |
| 3 | 184 | 1.2% |
| 90 | 136 | 0.9% |
| 93 | 131 | 0.8% |
| 94 | 125 | 0.8% |
| 91 | 125 | 0.8% |
| Other values (199) | 5085 |
Most occurring characters
| Value | Count | Frequency (%) |
| 7770 | ||
| n | 7770 | |
| m | 5372 | |
| i | 5372 | |
| 1 | 5275 | |
| s | 3190 | 5.8% |
| S | 2398 | 4.4% |
| o | 2398 | 4.4% |
| e | 2398 | 4.4% |
| a | 2398 | 4.4% |
| Other values (9) | 10406 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 54747 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 7770 | ||
| n | 7770 | |
| m | 5372 | |
| i | 5372 | |
| 1 | 5275 | |
| s | 3190 | 5.8% |
| S | 2398 | 4.4% |
| o | 2398 | 4.4% |
| e | 2398 | 4.4% |
| a | 2398 | 4.4% |
| Other values (9) | 10406 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 54747 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 7770 | ||
| n | 7770 | |
| m | 5372 | |
| i | 5372 | |
| 1 | 5275 | |
| s | 3190 | 5.8% |
| S | 2398 | 4.4% |
| o | 2398 | 4.4% |
| e | 2398 | 4.4% |
| a | 2398 | 4.4% |
| Other values (9) | 10406 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 54747 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 7770 | ||
| n | 7770 | |
| m | 5372 | |
| i | 5372 | |
| 1 | 5275 | |
| s | 3190 | 5.8% |
| S | 2398 | 4.4% |
| o | 2398 | 4.4% |
| e | 2398 | 4.4% |
| a | 2398 | 4.4% |
| Other values (9) | 10406 |
listed_in
Text
| Distinct | 491 |
|---|---|
| Distinct (%) | 6.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Length
| Max length | 79 |
|---|---|
| Median length | 58 |
| Mean length | 33.372458 |
| Min length | 6 |
Unique
| Unique | 143 ? |
|---|---|
| Unique (%) | 1.8% |
Sample
| 1st row | International TV Shows, TV Dramas, TV Sci-Fi & Fantasy |
|---|---|
| 2nd row | Dramas, International Movies |
| 3rd row | Horror Movies, International Movies |
| 4th row | Action & Adventure, Independent Movies, Sci-Fi & Fantasy |
| 5th row | Dramas |
| Value | Count | Frequency (%) |
| movies | 4985 | |
| tv | 4951 | |
| international | 3634 | |
| dramas | 2808 | 8.1% |
| shows | 2607 | 7.5% |
| 2235 | 6.5% | |
| comedies | 1988 | 5.7% |
| action | 870 | 2.5% |
| adventure | 870 | 2.5% |
| romantic | 864 | 2.5% |
| Other values (33) | 8763 |
Most occurring characters
| Value | Count | Frequency (%) |
| 26805 | 10.3% | |
| e | 22192 | 8.6% |
| i | 18859 | 7.3% |
| n | 18307 | 7.1% |
| a | 17600 | 6.8% |
| o | 17575 | 6.8% |
| s | 17298 | 6.7% |
| t | 13141 | 5.1% |
| r | 12645 | 4.9% |
| , | 9272 | 3.6% |
| Other values (33) | 85610 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 259304 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 26805 | 10.3% | |
| e | 22192 | 8.6% |
| i | 18859 | 7.3% |
| n | 18307 | 7.1% |
| a | 17600 | 6.8% |
| o | 17575 | 6.8% |
| s | 17298 | 6.7% |
| t | 13141 | 5.1% |
| r | 12645 | 4.9% |
| , | 9272 | 3.6% |
| Other values (33) | 85610 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 259304 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 26805 | 10.3% | |
| e | 22192 | 8.6% |
| i | 18859 | 7.3% |
| n | 18307 | 7.1% |
| a | 17600 | 6.8% |
| o | 17575 | 6.8% |
| s | 17298 | 6.7% |
| t | 13141 | 5.1% |
| r | 12645 | 4.9% |
| , | 9272 | 3.6% |
| Other values (33) | 85610 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 259304 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 26805 | 10.3% | |
| e | 22192 | 8.6% |
| i | 18859 | 7.3% |
| n | 18307 | 7.1% |
| a | 17600 | 6.8% |
| o | 17575 | 6.8% |
| s | 17298 | 6.7% |
| t | 13141 | 5.1% |
| r | 12645 | 4.9% |
| , | 9272 | 3.6% |
| Other values (33) | 85610 |
description
Text
| Distinct | 7752 |
|---|---|
| Distinct (%) | 99.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Length
| Max length | 248 |
|---|---|
| Median length | 240 |
| Mean length | 143.10129 |
| Min length | 61 |
Unique
| Unique | 7736 ? |
|---|---|
| Unique (%) | 99.6% |
Sample
| 1st row | In a future where the elite inhabit an island paradise far from the crowded slums, you get one chance to join the 3% saved from squalor. |
|---|---|
| 2nd row | After a devastating earthquake hits Mexico City, trapped survivors from all walks of life wait to be rescued while trying desperately to stay alive. |
| 3rd row | When an army recruit is found dead, his fellow soldiers are forced to confront a terrifying secret that's haunting their jungle island training camp. |
| 4th row | In a postapocalyptic world, rag-doll robots hide in fear from dangerous machines out to exterminate them, until a brave newcomer joins the group. |
| 5th row | A brilliant group of students become card-counting experts with the intent of swindling millions out of Las Vegas casinos by playing blackjack. |
| Value | Count | Frequency (%) |
| a | 10128 | 5.5% |
| the | 7181 | 3.9% |
| to | 5652 | 3.1% |
| and | 5585 | 3.0% |
| of | 4692 | 2.5% |
| in | 3857 | 2.1% |
| his | 3003 | 1.6% |
| with | 1972 | 1.1% |
| her | 1882 | 1.0% |
| an | 1727 | 0.9% |
| Other values (20204) | 139470 |
Most occurring characters
| Value | Count | Frequency (%) |
| 177385 | ||
| e | 104477 | 9.4% |
| a | 74649 | 6.7% |
| t | 71698 | 6.4% |
| i | 69304 | 6.2% |
| n | 65693 | 5.9% |
| o | 64011 | 5.8% |
| s | 63958 | 5.8% |
| r | 62394 | 5.6% |
| h | 42862 | 3.9% |
| Other values (107) | 315466 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 1111897 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 177385 | ||
| e | 104477 | 9.4% |
| a | 74649 | 6.7% |
| t | 71698 | 6.4% |
| i | 69304 | 6.2% |
| n | 65693 | 5.9% |
| o | 64011 | 5.8% |
| s | 63958 | 5.8% |
| r | 62394 | 5.6% |
| h | 42862 | 3.9% |
| Other values (107) | 315466 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 1111897 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 177385 | ||
| e | 104477 | 9.4% |
| a | 74649 | 6.7% |
| t | 71698 | 6.4% |
| i | 69304 | 6.2% |
| n | 65693 | 5.9% |
| o | 64011 | 5.8% |
| s | 63958 | 5.8% |
| r | 62394 | 5.6% |
| h | 42862 | 3.9% |
| Other values (107) | 315466 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 1111897 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 177385 | ||
| e | 104477 | 9.4% |
| a | 74649 | 6.7% |
| t | 71698 | 6.4% |
| i | 69304 | 6.2% |
| n | 65693 | 5.9% |
| o | 64011 | 5.8% |
| s | 63958 | 5.8% |
| r | 62394 | 5.6% |
| h | 42862 | 3.9% |
| Other values (107) | 315466 |
year_added
Real number (ℝ)
| Distinct | 14 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2018.495 |
| Minimum | 2008 |
|---|---|
| Maximum | 2021 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 91.1 KiB |
Quantile statistics
| Minimum | 2008 |
|---|---|
| 5-th percentile | 2016 |
| Q1 | 2018 |
| median | 2019 |
| Q3 | 2020 |
| 95-th percentile | 2020 |
| Maximum | 2021 |
| Range | 13 |
| Interquartile range (IQR) | 2 |
Descriptive statistics
| Standard deviation | 1.3875819 |
|---|---|
| Coefficient of variation (CV) | 0.0006874339 |
| Kurtosis | 2.6893542 |
| Mean | 2018.495 |
| Median Absolute Deviation (MAD) | 1 |
| Skewness | -1.0091554 |
| Sum | 15683706 |
| Variance | 1.9253835 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=14)
| Value | Count | Frequency (%) |
| 2019 | 2153 | |
| 2020 | 2009 | |
| 2018 | 1684 | |
| 2017 | 1222 | |
| 2016 | 440 | 5.7% |
| 2021 | 117 | 1.5% |
| 2015 | 88 | 1.1% |
| 2014 | 25 | 0.3% |
| 2011 | 13 | 0.2% |
| 2013 | 11 | 0.1% |
| Other values (4) | 8 | 0.1% |
| Value | Count | Frequency (%) |
| 2008 | 2 | < 0.1% |
| 2009 | 2 | < 0.1% |
| 2010 | 1 | < 0.1% |
| 2011 | 13 | 0.2% |
| 2012 | 3 | < 0.1% |
| 2013 | 11 | 0.1% |
| 2014 | 25 | 0.3% |
| 2015 | 88 | 1.1% |
| 2016 | 440 | 5.7% |
| 2017 | 1222 |
| Value | Count | Frequency (%) |
| 2021 | 117 | 1.5% |
| 2020 | 2009 | |
| 2019 | 2153 | |
| 2018 | 1684 | |
| 2017 | 1222 | |
| 2016 | 440 | 5.7% |
| 2015 | 88 | 1.1% |
| 2014 | 25 | 0.3% |
| 2013 | 11 | 0.1% |
| 2012 | 3 | < 0.1% |
month_added
Real number (ℝ)
| Distinct | 12 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 6.7849421 |
| Minimum | 1 |
|---|---|
| Maximum | 12 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 91.1 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 1 |
| Q1 | 4 |
| median | 7 |
| Q3 | 10 |
| 95-th percentile | 12 |
| Maximum | 12 |
| Range | 11 |
| Interquartile range (IQR) | 6 |
Descriptive statistics
| Standard deviation | 3.5912186 |
|---|---|
| Coefficient of variation (CV) | 0.52929245 |
| Kurtosis | -1.2811157 |
| Mean | 6.7849421 |
| Median Absolute Deviation (MAD) | 3 |
| Skewness | -0.12036778 |
| Sum | 52719 |
| Variance | 12.896851 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=12)
| Value | Count | Frequency (%) |
| 12 | 832 | |
| 10 | 785 | |
| 1 | 756 | |
| 11 | 738 | |
| 3 | 668 | |
| 9 | 618 | |
| 8 | 617 | |
| 7 | 600 | |
| 4 | 600 | |
| 5 | 543 | |
| Other values (2) | 1013 |
| Value | Count | Frequency (%) |
| 1 | 756 | |
| 2 | 471 | |
| 3 | 668 | |
| 4 | 600 | |
| 5 | 543 | |
| 6 | 542 | |
| 7 | 600 | |
| 8 | 617 | |
| 9 | 618 | |
| 10 | 785 |
| Value | Count | Frequency (%) |
| 12 | 832 | |
| 11 | 738 | |
| 10 | 785 | |
| 9 | 618 | |
| 8 | 617 | |
| 7 | 600 | |
| 6 | 542 | |
| 5 | 543 | |
| 4 | 600 | |
| 3 | 668 |
age_on_netflix
Real number (ℝ)
High correlation Zeros
| Distinct | 74 |
|---|---|
| Distinct (%) | 1.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 4.5595882 |
| Minimum | -3 |
|---|---|
| Maximum | 93 |
| Zeros | 2823 |
| Zeros (%) | 36.3% |
| Negative | 12 |
| Negative (%) | 0.2% |
| Memory size | 121.4 KiB |
Quantile statistics
| Minimum | -3 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 1 |
| Q3 | 5 |
| 95-th percentile | 21 |
| Maximum | 93 |
| Range | 96 |
| Interquartile range (IQR) | 5 |
Descriptive statistics
| Standard deviation | 8.734355 |
|---|---|
| Coefficient of variation (CV) | 1.9156017 |
| Kurtosis | 17.585079 |
| Mean | 4.5595882 |
| Median Absolute Deviation (MAD) | 1 |
| Skewness | 3.6754387 |
| Sum | 35428 |
| Variance | 76.288957 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0 | 2823 | |
| 1 | 1484 | |
| 2 | 643 | 8.3% |
| 3 | 437 | 5.6% |
| 4 | 336 | 4.3% |
| 5 | 226 | 2.9% |
| 6 | 217 | 2.8% |
| 7 | 169 | 2.2% |
| 8 | 161 | 2.1% |
| 9 | 139 | 1.8% |
| Other values (64) | 1135 |
| Value | Count | Frequency (%) |
| -3 | 1 | < 0.1% |
| -2 | 1 | < 0.1% |
| -1 | 10 | 0.1% |
| 0 | 2823 | |
| 1 | 1484 | |
| 2 | 643 | 8.3% |
| 3 | 437 | 5.6% |
| 4 | 336 | 4.3% |
| 5 | 226 | 2.9% |
| 6 | 217 | 2.8% |
| Value | Count | Frequency (%) |
| 93 | 1 | < 0.1% |
| 75 | 2 | |
| 74 | 3 | |
| 73 | 3 | |
| 72 | 3 | |
| 71 | 2 | |
| 70 | 1 | < 0.1% |
| 66 | 2 | |
| 65 | 2 | |
| 64 | 2 |
bigrams
Unsupported
Rejected Unsupported
| Missing | 0 |
|---|---|
| Missing (%) | 0.0% |
| Memory size | 121.4 KiB |
Interactions
Correlations
| age_on_netflix | month_added | rating | release_year | type | year_added | |
|---|---|---|---|---|---|---|
| age_on_netflix | 1.000 | -0.115 | 0.135 | -0.861 | 0.175 | 0.044 |
| month_added | -0.115 | 1.000 | 0.045 | 0.015 | 0.020 | -0.123 |
| rating | 0.135 | 0.045 | 1.000 | 0.128 | 0.344 | 0.098 |
| release_year | -0.861 | 0.015 | 0.128 | 1.000 | 0.159 | 0.365 |
| type | 0.175 | 0.020 | 0.344 | 0.159 | 1.000 | 0.067 |
| year_added | 0.044 | -0.123 | 0.098 | 0.365 | 0.067 | 1.000 |
Missing values
A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
Sample
| show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | year_added | month_added | age_on_netflix | bigrams | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | s1 | TV Show | 3% | Unknown | João Miguel, Bianca Comparato, Michel Gomes, Rodolfo Valente, Vaneza Oliveira, Rafael Lozano, Viviane Porto, Mel Fronckowiak, Sergio Mamberti, Zezé Motta, Celso Frateschi | Brazil | 2020-08-14 | 2020 | TV-MA | 4 Seasons | International TV Shows, TV Dramas, TV Sci-Fi & Fantasy | In a future where the elite inhabit an island paradise far from the crowded slums, you get one chance to join the 3% saved from squalor. | 2020 | 8 | 0 | [(in, a), (a, future), (future, where), (where, the), (the, elite), (elite, inhabit), (inhabit, an), (an, island), (island, paradise), (paradise, far), (far, from), (from, the), (the, crowded), (crowded, slums,), (slums,, you), (you, get), (get, one), (one, chance), (chance, to), (to, join), (join, the), (the, 3%), (3%, saved), (saved, from), (from, squalor.)] |
| 1 | s2 | Movie | 7:19 | Jorge Michel Grau | Demián Bichir, Héctor Bonilla, Oscar Serrano, Azalia Ortiz, Octavio Michel, Carmen Beato | Mexico | 2016-12-23 | 2016 | TV-MA | 93 min | Dramas, International Movies | After a devastating earthquake hits Mexico City, trapped survivors from all walks of life wait to be rescued while trying desperately to stay alive. | 2016 | 12 | 0 | [(after, a), (a, devastating), (devastating, earthquake), (earthquake, hits), (hits, mexico), (mexico, city,), (city,, trapped), (trapped, survivors), (survivors, from), (from, all), (all, walks), (walks, of), (of, life), (life, wait), (wait, to), (to, be), (be, rescued), (rescued, while), (while, trying), (trying, desperately), (desperately, to), (to, stay), (stay, alive.)] |
| 2 | s3 | Movie | 23:59 | Gilbert Chan | Tedd Chan, Stella Chung, Henley Hii, Lawrence Koh, Tommy Kuan, Josh Lai, Mark Lee, Susan Leong, Benjamin Lim | Singapore | 2018-12-20 | 2011 | R | 78 min | Horror Movies, International Movies | When an army recruit is found dead, his fellow soldiers are forced to confront a terrifying secret that's haunting their jungle island training camp. | 2018 | 12 | 7 | [(when, an), (an, army), (army, recruit), (recruit, is), (is, found), (found, dead,), (dead,, his), (his, fellow), (fellow, soldiers), (soldiers, are), (are, forced), (forced, to), (to, confront), (confront, a), (a, terrifying), (terrifying, secret), (secret, that's), (that's, haunting), (haunting, their), (their, jungle), (jungle, island), (island, training), (training, camp.)] |
| 3 | s4 | Movie | 9 | Shane Acker | Elijah Wood, John C. Reilly, Jennifer Connelly, Christopher Plummer, Crispin Glover, Martin Landau, Fred Tatasciore, Alan Oppenheimer, Tom Kane | United States | 2017-11-16 | 2009 | PG-13 | 80 min | Action & Adventure, Independent Movies, Sci-Fi & Fantasy | In a postapocalyptic world, rag-doll robots hide in fear from dangerous machines out to exterminate them, until a brave newcomer joins the group. | 2017 | 11 | 8 | [(in, a), (a, postapocalyptic), (postapocalyptic, world,), (world,, rag-doll), (rag-doll, robots), (robots, hide), (hide, in), (in, fear), (fear, from), (from, dangerous), (dangerous, machines), (machines, out), (out, to), (to, exterminate), (exterminate, them,), (them,, until), (until, a), (a, brave), (brave, newcomer), (newcomer, joins), (joins, the), (the, group.)] |
| 4 | s5 | Movie | 21 | Robert Luketic | Jim Sturgess, Kevin Spacey, Kate Bosworth, Aaron Yoo, Liza Lapira, Jacob Pitts, Laurence Fishburne, Jack McGee, Josh Gad, Sam Golzari, Helen Carey, Jack Gilpin | United States | 2020-01-01 | 2008 | PG-13 | 123 min | Dramas | A brilliant group of students become card-counting experts with the intent of swindling millions out of Las Vegas casinos by playing blackjack. | 2020 | 1 | 12 | [(a, brilliant), (brilliant, group), (group, of), (of, students), (students, become), (become, card-counting), (card-counting, experts), (experts, with), (with, the), (the, intent), (intent, of), (of, swindling), (swindling, millions), (millions, out), (out, of), (of, las), (las, vegas), (vegas, casinos), (casinos, by), (by, playing), (playing, blackjack.)] |
| 5 | s6 | TV Show | 46 | Serdar Akar | Erdal Beşikçioğlu, Yasemin Allen, Melis Birkan, Saygın Soysal, Berkan Şal, Metin Belgin, Ayça Eren, Selin Uludoğan, Özay Fecht, Suna Yıldızoğlu | Turkey | 2017-07-01 | 2016 | TV-MA | 1 Season | International TV Shows, TV Dramas, TV Mysteries | A genetics professor experiments with a treatment for his comatose sister that blends medical and shamanic cures, but unlocks a shocking side effect. | 2017 | 7 | 1 | [(a, genetics), (genetics, professor), (professor, experiments), (experiments, with), (with, a), (a, treatment), (treatment, for), (for, his), (his, comatose), (comatose, sister), (sister, that), (that, blends), (blends, medical), (medical, and), (and, shamanic), (shamanic, cures,), (cures,, but), (but, unlocks), (unlocks, a), (a, shocking), (shocking, side), (side, effect.)] |
| 6 | s7 | Movie | 122 | Yasir Al Yasiri | Amina Khalil, Ahmed Dawood, Tarek Lotfy, Ahmed El Fishawy, Mahmoud Hijazi, Jihane Khalil, Asmaa Galal, Tara Emad | Egypt | 2020-06-01 | 2019 | TV-MA | 95 min | Horror Movies, International Movies | After an awful accident, a couple admitted to a grisly hospital are separated and must find each other to escape — before death finds them. | 2020 | 6 | 1 | [(after, an), (an, awful), (awful, accident,), (accident,, a), (a, couple), (couple, admitted), (admitted, to), (to, a), (a, grisly), (grisly, hospital), (hospital, are), (are, separated), (separated, and), (and, must), (must, find), (find, each), (each, other), (other, to), (to, escape), (escape, —), (—, before), (before, death), (death, finds), (finds, them.)] |
| 7 | s8 | Movie | 187 | Kevin Reynolds | Samuel L. Jackson, John Heard, Kelly Rowan, Clifton Collins Jr., Tony Plana | United States | 2019-11-01 | 1997 | R | 119 min | Dramas | After one of his high school students attacks him, dedicated teacher Trevor Garfield grows weary of the gang warfare in the New York City school system and moves to California to teach there, thinking it must be a less hostile environment. | 2019 | 11 | 22 | [(after, one), (one, of), (of, his), (his, high), (high, school), (school, students), (students, attacks), (attacks, him,), (him,, dedicated), (dedicated, teacher), (teacher, trevor), (trevor, garfield), (garfield, grows), (grows, weary), (weary, of), (of, the), (the, gang), (gang, warfare), (warfare, in), (in, the), (the, new), (new, york), (york, city), (city, school), (school, system), (system, and), (and, moves), (moves, to), (to, california), (california, to), (to, teach), (teach, there,), (there,, thinking), (thinking, it), (it, must), (must, be), (be, a), (a, less), (less, hostile), (hostile, environment.)] |
| 8 | s9 | Movie | 706 | Shravan Kumar | Divya Dutta, Atul Kulkarni, Mohan Agashe, Anupam Shyam, Raayo S. Bakhirta, Yashvit Sancheti, Greeva Kansara, Archan Trivedi, Rajiv Pathak | India | 2019-04-01 | 2019 | TV-14 | 118 min | Horror Movies, International Movies | When a doctor goes missing, his psychiatrist wife treats the bizarre medical condition of a psychic patient, who knows much more than he's leading on. | 2019 | 4 | 0 | [(when, a), (a, doctor), (doctor, goes), (goes, missing,), (missing,, his), (his, psychiatrist), (psychiatrist, wife), (wife, treats), (treats, the), (the, bizarre), (bizarre, medical), (medical, condition), (condition, of), (of, a), (a, psychic), (psychic, patient,), (patient,, who), (who, knows), (knows, much), (much, more), (more, than), (than, he's), (he's, leading), (leading, on.)] |
| 9 | s10 | Movie | 1920 | Vikram Bhatt | Rajneesh Duggal, Adah Sharma, Indraneil Sengupta, Anjori Alagh, Rajendranath Zutshi, Vipin Sharma, Amin Hajee, Shri Vallabh Vyas | India | 2017-12-15 | 2008 | TV-MA | 143 min | Horror Movies, International Movies, Thrillers | An architect and his wife move into a castle that is slated to become a luxury hotel. But something inside is determined to stop the renovation. | 2017 | 12 | 9 | [(an, architect), (architect, and), (and, his), (his, wife), (wife, move), (move, into), (into, a), (a, castle), (castle, that), (that, is), (is, slated), (slated, to), (to, become), (become, a), (a, luxury), (luxury, hotel.), (hotel., but), (but, something), (something, inside), (inside, is), (is, determined), (determined, to), (to, stop), (stop, the), (the, renovation.)] |
| show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | year_added | month_added | age_on_netflix | bigrams | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 7777 | s7778 | TV Show | Zombie Dumb | Unknown | Unknown | United States | 2019-07-01 | 2018 | TV-Y7 | 2 Seasons | Kids' TV, Korean TV Shows, TV Comedies | While living alone in a spooky town, a young girl befriends a motley crew of zombie children with diverse personalities. | 2019 | 7 | 1 | [(while, living), (living, alone), (alone, in), (in, a), (a, spooky), (spooky, town,), (town,, a), (a, young), (young, girl), (girl, befriends), (befriends, a), (a, motley), (motley, crew), (crew, of), (of, zombie), (zombie, children), (children, with), (with, diverse), (diverse, personalities.)] |
| 7778 | s7779 | Movie | Zombieland | Ruben Fleischer | Jesse Eisenberg, Woody Harrelson, Emma Stone, Abigail Breslin, Amber Heard, Bill Murray, Derek Graf | United States | 2019-11-01 | 2009 | R | 88 min | Comedies, Horror Movies | Looking to survive in a world taken over by zombies, a dorky college student teams with an urban roughneck and a pair of grifter sisters. | 2019 | 11 | 10 | [(looking, to), (to, survive), (survive, in), (in, a), (a, world), (world, taken), (taken, over), (over, by), (by, zombies,), (zombies,, a), (a, dorky), (dorky, college), (college, student), (student, teams), (teams, with), (with, an), (an, urban), (urban, roughneck), (roughneck, and), (and, a), (a, pair), (pair, of), (of, grifter), (grifter, sisters.)] |
| 7779 | s7780 | TV Show | Zona Rosa | Unknown | Manu NNa, Ana Julia Yeyé, Ray Contreras, Pablo Morán | Mexico | 2019-11-26 | 2019 | TV-MA | 1 Season | International TV Shows, Spanish-Language TV Shows, Stand-Up Comedy & Talk Shows | An assortment of talent takes the stage for a night of honest stand-up featuring four of Mexico's funniest LGBTQ comedians. | 2019 | 11 | 0 | [(an, assortment), (assortment, of), (of, talent), (talent, takes), (takes, the), (the, stage), (stage, for), (for, a), (a, night), (night, of), (of, honest), (honest, stand-up), (stand-up, featuring), (featuring, four), (four, of), (of, mexico's), (mexico's, funniest), (funniest, lgbtq), (lgbtq, comedians.)] |
| 7780 | s7781 | Movie | Zoo | Shlok Sharma | Shashank Arora, Shweta Tripathi, Rahul Kumar, Gopal K. Singh, Yogesh Kurme, Prince Daniel | India | 2018-07-01 | 2018 | TV-MA | 94 min | Dramas, Independent Movies, International Movies | A drug dealer starts having doubts about his trade as his brother, his client, and two rappers from the slums each battle their own secret addictions. | 2018 | 7 | 0 | [(a, drug), (drug, dealer), (dealer, starts), (starts, having), (having, doubts), (doubts, about), (about, his), (his, trade), (trade, as), (as, his), (his, brother,), (brother,, his), (his, client,), (client,, and), (and, two), (two, rappers), (rappers, from), (from, the), (the, slums), (slums, each), (each, battle), (battle, their), (their, own), (own, secret), (secret, addictions.)] |
| 7781 | s7782 | Movie | Zoom | Peter Hewitt | Tim Allen, Courteney Cox, Chevy Chase, Kate Mara, Ryan Newman, Michael Cassidy, Spencer Breslin, Rip Torn, Kevin Zegers | United States | 2020-01-11 | 2006 | PG | 88 min | Children & Family Movies, Comedies | Dragged from civilian life, a former superhero must train a new crop of youthful saviors when the military preps for an attack by a familiar villain. | 2020 | 1 | 14 | [(dragged, from), (from, civilian), (civilian, life,), (life,, a), (a, former), (former, superhero), (superhero, must), (must, train), (train, a), (a, new), (new, crop), (crop, of), (of, youthful), (youthful, saviors), (saviors, when), (when, the), (the, military), (military, preps), (preps, for), (for, an), (an, attack), (attack, by), (by, a), (a, familiar), (familiar, villain.)] |
| 7782 | s7783 | Movie | Zozo | Josef Fares | Imad Creidi, Antoinette Turk, Elias Gergi, Carmen Lebbos, Viktor Axelsson, Charbel Iskandar, Yasmine Awad | Sweden, Czech Republic, United Kingdom, Denmark, Netherlands | 2020-10-19 | 2005 | TV-MA | 99 min | Dramas, International Movies | When Lebanon's Civil War deprives Zozo of his family, he's left with grief and little means as he escapes to Sweden in search of his grandparents. | 2020 | 10 | 15 | [(when, lebanon's), (lebanon's, civil), (civil, war), (war, deprives), (deprives, zozo), (zozo, of), (of, his), (his, family,), (family,, he's), (he's, left), (left, with), (with, grief), (grief, and), (and, little), (little, means), (means, as), (as, he), (he, escapes), (escapes, to), (to, sweden), (sweden, in), (in, search), (search, of), (of, his), (his, grandparents.)] |
| 7783 | s7784 | Movie | Zubaan | Mozez Singh | Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanana, Manish Chaudhary, Meghna Malik, Malkeet Rauni, Anita Shabdish, Chittaranjan Tripathy | India | 2019-03-02 | 2015 | TV-14 | 111 min | Dramas, International Movies, Music & Musicals | A scrappy but poor boy worms his way into a tycoon's dysfunctional family, while facing his fear of music and the truth about his past. | 2019 | 3 | 4 | [(a, scrappy), (scrappy, but), (but, poor), (poor, boy), (boy, worms), (worms, his), (his, way), (way, into), (into, a), (a, tycoon's), (tycoon's, dysfunctional), (dysfunctional, family,), (family,, while), (while, facing), (facing, his), (his, fear), (fear, of), (of, music), (music, and), (and, the), (the, truth), (truth, about), (about, his), (his, past.)] |
| 7784 | s7785 | Movie | Zulu Man in Japan | Unknown | Nasty C | United States | 2020-09-25 | 2019 | TV-MA | 44 min | Documentaries, International Movies, Music & Musicals | In this documentary, South African rapper Nasty C hits the stage and streets of Tokyo, introducing himself to the city's sights, sounds and culture. | 2020 | 9 | 1 | [(in, this), (this, documentary,), (documentary,, south), (south, african), (african, rapper), (rapper, nasty), (nasty, c), (c, hits), (hits, the), (the, stage), (stage, and), (and, streets), (streets, of), (of, tokyo,), (tokyo,, introducing), (introducing, himself), (himself, to), (to, the), (the, city's), (city's, sights,), (sights,, sounds), (sounds, and), (and, culture.)] |
| 7785 | s7786 | TV Show | Zumbo's Just Desserts | Unknown | Adriano Zumbo, Rachel Khoo | Australia | 2020-10-31 | 2019 | TV-PG | 1 Season | International TV Shows, Reality TV | Dessert wizard Adriano Zumbo looks for the next “Willy Wonka” in this tense competition that finds skilled amateurs competing for a $100,000 prize. | 2020 | 10 | 1 | [(dessert, wizard), (wizard, adriano), (adriano, zumbo), (zumbo, looks), (looks, for), (for, the), (the, next), (next, “willy), (“willy, wonka”), (wonka”, in), (in, this), (this, tense), (tense, competition), (competition, that), (that, finds), (finds, skilled), (skilled, amateurs), (amateurs, competing), (competing, for), (for, a), (a, $100,000), ($100,000, prize.)] |
| 7786 | s7787 | Movie | ZZ TOP: THAT LITTLE OL' BAND FROM TEXAS | Sam Dunn | Unknown | United Kingdom, Canada, United States | 2020-03-01 | 2019 | TV-MA | 90 min | Documentaries, Music & Musicals | This documentary delves into the mystique behind the blues-rock trio and explores how the enigmatic band created their iconic look and sound. | 2020 | 3 | 1 | [(this, documentary), (documentary, delves), (delves, into), (into, the), (the, mystique), (mystique, behind), (behind, the), (the, blues-rock), (blues-rock, trio), (trio, and), (and, explores), (explores, how), (how, the), (the, enigmatic), (enigmatic, band), (band, created), (created, their), (their, iconic), (iconic, look), (look, and), (and, sound.)] |